Research On Support Vector Machines Based Spare Parts Demand Of Yankuang Group

Yankuang Group is an extra-large State-Owned-Enterprise mainlyengaged in coal mining, coal chemical industry, power generation andaluminum. Relying on superior geographical location, it is commitment toreform, and gradually becomes an influential international enterprise.Currently, Yankuang Group actively changes the structure of productioninstead of the single coal mining structure. It has formed the structureof coal mining, coal chemical industry, power generation and aluminum.Yankuang has developed the new growth situation with3Industrial Parksin Yankuang HQs areas and5Production Bases outside Shandong respectivelylocated in Yulin (Shaanxi), Ordos(Inner Mongolia), Guizhou province,Xinjiang Province and Australia, which involves coal mining&sales, coalchemical industry, power generation&aluminum and machinerymanufacturing. In2011, Yankuang ranked121st among China’s Top500Enterprises with total assets of RMB70billion and93,000employees. Withthe maturity of the coal chemical, power generation and aluminum,equipment diverse characteristics significantly, and spare parts typescomplicate. Business inventories begins to face enormous pressure, spareparts management is facing unprecedented challenges. Strengthening themanagement of spare parts becomes one of the ways to reduce costs, andimprove efficiency.Equipment management is an important part of internal management, theeffect of the internal management will determine the competitiveness ofenterprises. Equipment is an important factor of production ofcapital-intensive enterprises, and the equipment is mainly relies on thetools of production activities. Therefore, the equipment management isan effective means of corporate economic growth. A key element in theDevice Manager is the spare parts management. Spare parts management canguarantee the demand for production and maintenance of spare parts, andimprove equipment security and persistence. It can guarantee the supplyof spare parts and reduce inventory costs, in order to achieve total costreduction. Spare parts inventory management involves the classificationof spare parts, spare parts demand forecasting, spare parts inventoryoptimization, and many other.Support Vector Machine was first used by Vapnik in1963.It was usedas a classification technique, mainly to solve pattern recognitionproblems. Through the development of statistic learning theory, thesupport vector machine show a good generalization ability, when it is usedto solve the problem of small sample. This paper attempts to apply supportvector machine method.Through training of Yankuang Group historicaldata,we will get a perfect prediction machine, to predict the forecast data set. Then after the analyses of error, we can verify the feasibilityof support vector machines.Based on this, this paper uses the method of combination ofqualitative and quantitative analysis, and combination of empiricalresearch and normative studies. At first, this paper gets the summary ofthe domestic and foreign spare parts demand forecasting studies tounderstand the research status, lack of discovery research. At the sametime, it show us the inventory management, and support vector machinetheory. Above all, this paper has solved the problems of Yankuang Group spareparts demand forecasting, and establishes the model of Yankuang Groupspare parts demand forecasting. Then it verifies the feasibility of themodel. At last, the paper provides feasible suggestion for coal companiesabout spare parts inventory management.